Financial Data Mapping Service for Real-Time Distribution
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Solution Overview
Problem
Current systems for processing and distributing financial data lack the ability to provide customized, real-time data distribution to individual users, failing to efficiently map and format data according to user specifications for use in various applications.
Innovation Solution
The system enables users to select and map financial data from feeds into standardized formats, allowing for real-time distribution and processing, with features like data filtering, formatting, and caching to ensure data is available when needed, and allows data to be remapped and sent back to the source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If financial data is distributed in standardized format from data sources, then data availability and real-time processing are improved, but adaptability to user-specific application formats deteriorates
Solution Approach 1:
The patent introduces a data mapping service as an intermediary component between the standardized data source and user applications. This mediator receives standardized financial data records, translates them into user-specific formats based on application requirements, and delivers the customized data to various applications. This resolves the contradiction by maintaining standardized data flow for real-time processing while adding format adaptability through the mapping service layer.
Solution Approach 2:
The system implements dynamic data format adaptation where the mapping service can adjust data structure, field order, and formatting based on real-time application requirements. The mapping configurations are flexible and can be modified without affecting the standardized data source, allowing the system to adapt to changing user needs while maintaining efficient real-time data distribution.
2Adaptability or versatility
If data is customized and mapped to multiple formats for different applications, then adaptability to user needs is improved, but system complexity increases
Solution Approach 1:
The patent divides the data processing system into distinct functional segments: a data source layer providing standardized formats, a mapping service layer handling format translation, and an application layer consuming customized data. This segmentation isolates complexity to the mapping service while keeping data source and application interfaces simple, making the overall system manageable despite multi-format requirements.
Solution Approach 2:
The data mapping service is designed as a universal component that handles multiple data format conversions through a single service layer. Rather than creating separate processing systems for each application format, the mapping service provides multi-functional capabilities to translate standardized data into various user-specific formats, reducing overall system complexity while maintaining high adaptability.
3Adaptability or versatility
If data mapping and filtering operations are performed in real-time, then data relevance and user-specific customization are improved, but processing time and computational resources increase
Solution Approach 1:
The system performs data mapping and filtering operations in advance during the data reception phase, before the data is needed by applications. By pre-processing and preparing customized data formats when data arrives from the source, the system minimizes processing delays and ensures data is ready for immediate use by applications without significant time loss.
Data Source
AI summary
Improved systems, methods, and programs for customized distribution of data, particularly financial data. Individual users of networked computer systems have the capability to select and receive data from data streams produced by sources and made available simultaneously and in standardized format to numbers of client terminals. Selected data is mapped according to individual user specifications and may be used in client applications such as databases or spreadsheets, and stored in caches until users are ready to receive it. Data may be formatted and sent back to the stream source for use in applications operated at the source. The system also facilitates checking of data integrity, in particular by comparing sequences of records sent by the source and received by the client system.